× Welcome to frontrun me, the premier site for visualizing Ethereum gas auctions. These gas auctions are often bids by frontrunners, arbitrageurs, and other programmatic network actors that seek to exploit inefficiencies in on-chain systems, ultimately profiting miners. On this site, we monitor these behaviors on the network in real-time as these bots compete for block priority in rapid-fire all-pay auctions*, showing users and mechanism designers the potential rent-seeking economy created by orderbook inefficiencies on-chain. Timing data is sourced from a global network of 8 nodes peered deeply with Ethereum. Read our full paper!
*Modern auctions are a special kind of all-pay auction, in which the winner of the auction pays some constant percentage of their bid; they do not pay full gas, as they do not pay for execution, but they must pay for attempted execution.

WARNING: THIS IS AN ALPHA VERSION OF THE SITE WITH PRELIMINARY DATA AND KNOWN BUGS. Use at your own risk and follow @ProjectChicago_ for announcements on release and more data being added.

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Individual Real-Time Auction Data


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Note: only auctions with a single detected "winner" (mined with 2+ log events) are displayed in this view. Other auctions may contain multiple sub-auctions, as the split is heuristic.

Gas Auction #665 - 2018-09-24 15:27:34 to 15:28:04; Start Time 1537802854.3404822

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 110.355008853 () 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/17098 22000 0xc8892f9b25b9e8c52f9fcc4ea17ebb59de967d8c1f52259c335ae64751a3ac35
0.007 110.355008853 (0.0) 0xA045E11fB1551D7196B5B0526431688EfD49CFEA/7358 22000 0xe30f7ddbbdc462a48b1a8e57060942d0127a8acbca520f723ad2b8f275877cb5
0.515 5.138396366 (-182.20367178106315) 0xaDA1ED8Dea59b7B082937460C0863AbFFbB0484F/11269 800000 0x23b5ae1326a04c6e6f1f55a60e4195c98f943ff943137ccc6f89fd038e5ce1b7
0.767 102.000000000 (180.81585485582028) 0x0fD081e3Bb178dc45c0cb23202069ddA57064258/161822 105000 0x183e344cd340d4419f90525d654d2e89c6272fe68566702e75587f1a325016b4
3.745 11.215378028 (-160.3750719262669) 0x18a0451Ea56Fd4FF58f59837e9EC30f346ffDCa5/1886 300000 0xe4179e1e41414b0d1b3539f0be1f61222b92215ea78c5a951c7a7d1a5701b7f3
5.299 102.000000000 (160.3750719262669) 0x0fD081e3Bb178dc45c0cb23202069ddA57064258/161823 105000 0xeb2b02aca4531f1437dd2f6fedeeebb8cc782f310fb01d06f3a065e9d08a21ad
7.660 13.523332311 (-153.1754078056063) 0x3F2a954e94f4FC65c9f71c049aA5d63eBb7b19b7/6527 800000 0xec744dc464422cdcf4b39c92a82ccca3192d3ce3e88a3bdb667b6e41d6491ce7
8.643 7.000000000 (-63.569913619764904) 0x3F2a954e94f4FC65c9f71c049aA5d63eBb7b19b7/6528 800000 0x0775f7422dd3cd37602793600a592b7438b42f35a417e4523ffdf4da33baf580
30.264 9.948281860 (34.79151319707873) 0x3F2a954e94f4FC65c9f71c049aA5d63eBb7b19b7/6528 800000 0x210388164f1f9dfd2ab5bd93151d146b055e4712a9dc10d447fb13b67b224623
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This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE-1650441.
We would also like to thank NSF CNS-1330599, CNS-1514163, CNS-1564102, and CNS-1704615, ARL W911NF-16-1-0145, and IC3 Industry Partners.
Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors(s) and do not necessarily reflect the views of the National Science Foundation.